%0 Journal Article %A ZHOU Min %T Distance-based adaptive k particle swarm optimization %D 2011 %R %J Computer Engineering and Applications %P 43-45 %V 47 %N 15 %X The classical Particle Swarm Optimization(PSO) neglects the difference among particles and uses a fixed inertia weight in one generation.To cope with this issue,a novel method called(k,l) PSO is proposed in this paper.The(k,l) PSO chooses one of the top k particles as the global best particle according to the roulette strategy and tunes the inertia weight value according to the distance between the current particle and the global best particle.Several classical benchmark functions are used to evaluate the(k,l) PSO.The experiments demonstrate the efficiency and effectiveness of the proposed(k,l) PSO.
%U http://cea.ceaj.org/EN/abstract/article_26541.shtml